CN114549217A

CN114549217A - Credit data generation method and device, computer equipment and readable storage medium

Info

Publication number: CN114549217A
Application number: CN202210158908.XA
Authority: CN
Inventors: 顾巧娴
Original assignee: Ping An Medical and Healthcare Management Co Ltd
Current assignee: Ping An Medical and Healthcare Management Co Ltd
Priority date: 2022-02-21
Filing date: 2022-02-21
Publication date: 2022-05-27

Abstract

The application discloses a credit data generation method, a credit data generation device, computer equipment and a readable storage medium, relates to the technical field of intelligent medical treatment, and can be used for calculating credit scores of mechanisms to be evaluated and improving the transmission accuracy and the generation efficiency of credit data. The method comprises the following steps: acquiring data to be rated of a mechanism to be rated based on the current rating requirement, and inquiring an appointed rating rule corresponding to the data to be rated in the rating rule according to a preset regular expression; determining an appointed index value and an appointed index attribute corresponding to an appointed grading rule in a preset database, and calculating the credit score of the mechanism to be graded according to the appointed index value and the appointed index attribute; inquiring a plurality of preset score intervals in the current rating requirement, determining a target preset score interval with a credit score hitting in the preset score intervals, and taking a credit grade corresponding to the target preset score interval as credit data of an organization to be rated; and sending the credit data to a terminal corresponding to the mechanism to be evaluated for display.

Description

Credit data generation method and device, computer equipment and readable storage medium

Technical Field

The present application relates to the field of smart medical technology, and in particular, to a credit data generation method, apparatus, computer device, and readable storage medium.

Background

With the continuous development of internet technology and the gradual progress of medical level, a third party payment mechanism is introduced in medical insurance management and operation, so that the impulse of inducing excessive supply or excessive consumption of medical insurance participants of fixed-point medical institutions or fixed-point retail drug stores is increased on the basis of effectively guaranteeing the medical insurance rights and interests of the participants, and even the risk of cheating the medical insurance fund by using various cheating means is increased. Therefore, at present, many platforms can build an integrity system for medical institutions, generate credit management operation procedures, generate credit data of the medical institutions, perform credit management on the medical institutions, and reduce the risk of cheating on medical insurance funds.

In the related technology, related workers participating in credit evaluation in a platform need to perform activities such as offline inquiry, research and inspection, and finally data collection and sorting are performed on offline inquired data, and the offline inquired data are summarized into an integrity system to be scored, so that credit data of a medical institution are generated.

In the process of implementing the invention, the inventor finds that the related art has at least the following technical problems:

the platform can send a large amount of manpower to collect relevant data under the line, and the condition of data loss, recording error and the like can be generated when the data are collected under the manpower line, so that the data used for scoring have deviation with the actual condition of a medical institution, and the generation efficiency and the accuracy rate of the credit data are low.

Disclosure of Invention

In view of this, the present application provides a credit data generation method, an apparatus, a computer device and a readable storage medium, and mainly aims to solve the problems that data loss, recording errors and the like occur in data collected manually on-line at present, so that data used for scoring has deviation from the actual situation of a medical institution, and the generation efficiency and accuracy of credit data are low.

According to a first aspect of the present application, there is provided a credit data generation method, including:

acquiring data to be rated of a mechanism to be rated based on a current rating requirement, and inquiring an appointed rating rule corresponding to the data to be rated in the rating rule according to a preset regular expression;

determining an appointed index value and an appointed index attribute corresponding to the appointed grading rule in a preset database, and calculating the credit score of the mechanism to be graded according to the appointed index value and the appointed index attribute;

inquiring a plurality of preset score intervals in the current rating requirement, determining a target preset score interval in which the credit score hits in the preset score intervals, and taking the credit grade corresponding to the target preset score interval as credit data of the organization to be rated;

and sending the credit data to a terminal corresponding to the mechanism to be evaluated for display.

Optionally, the obtaining of the data to be rated of the organization to be rated based on the current rating requirement includes:

acquiring basic information uploaded by the mechanism to be rated based on the current rating requirement, and comparing the basic information with the current rating requirement to obtain a first comparison result;

when the first comparison result indicates that the basic information does not meet the current rating requirement, generating an audit failure prompt and sending the audit failure prompt to the to-be-rated mechanism for displaying, wherein the audit failure prompt is used for indicating the to-be-rated mechanism to upload the basic information again;

and when the first comparison result indicates that the basic information meets the rating requirement, calling an external system connection interface, acquiring abnormal information of the mechanism to be rated, and extracting the rating content indicated by the current rating requirement from the basic data and the abnormal information to serve as the data to be rated.

Optionally, the determining, in a preset database, an assigned index value and an assigned index attribute corresponding to the assigned scoring rule, and calculating a credit score of the to-be-rated organization according to the assigned index value and the assigned index attribute includes:

inquiring name tags of all index values and all index attributes in the preset database, and extracting the index values and the index attributes of which the name tags are the same as the specified scoring rules as the specified index values and the specified index attributes;

comparing the data to be graded with the specified grading rule to obtain a second comparison result, inquiring a specified index number value hit by the second comparison result, and taking the specified index number value as the initial grading;

and extracting a score proportion from the specified index attribute corresponding to the specified index value, calculating the product of the score proportion and the initial score, and taking the product as the credit score of the mechanism to be rated.

Optionally, after querying a plurality of preset score intervals in the current rating requirement, determining a target preset score interval in which the credit score hits in the plurality of preset score intervals, and using a credit level corresponding to the target preset score interval as credit data of the organization to be rated, the method further includes:

comparing the credit data with a first preset grade threshold value to generate a third comparison result, and adding a display label for the mechanism to be rated corresponding to the credit data based on the third comparison result;

identifying the display label of the mechanism to be identified, extracting the mechanism to be identified with the display label content as the incentive to form a credit red list, and extracting the mechanism to be identified with the display label content as the correction to form a credit black list;

and sending the credit red list and the credit blacklist to a display terminal database so that a display terminal calls the display list in the display terminal database to display.

Optionally, adding a display tag to the to-be-rated organization corresponding to the credit data based on the third comparison result, including:

if the third comparison result indicates that the credit data is greater than or equal to the first preset grade threshold, adding a display label with excited content to the mechanism to be graded corresponding to the credit data;

and if the third comparison result indicates that the credit data is smaller than the first preset level threshold, comparing the credit data with a second preset level threshold to obtain a fourth comparison result, and adding a display label with the corrected content to the mechanism to be evaluated corresponding to the credit data when the fourth comparison result indicates that the credit data is smaller than the second preset level threshold.

Optionally, after the credit data is sent to a terminal corresponding to the organization to be assessed for display, the method further includes:

responding to a credit complaint request triggered by the to-be-rated mechanism, acquiring to-be-rated nuclear data uploaded by the to-be-rated mechanism for credit auditing, and obtaining an auditing result;

and when the audit result indicates that the to-be-audited data meet the audit specification, calling a display database of the display terminal, deleting the organization name of the to-be-rated organization in the display database, and finishing the display of the to-be-rated organization on the credit blacklist.

Optionally, the method further comprises:

the method comprises the steps of obtaining credit data of all organizations to be rated, obtaining a plurality of credit data, sequencing the credit data according to the numerical value from high to low, sending service data and the credit data corresponding to all the sequenced organizations to be rated to a display terminal for displaying, wherein the service data are all operation data corresponding to the organizations to be rated;

counting the current time point, and determining the historical time point for displaying the service data and the credit data corresponding to the mechanism to be evaluated last time;

and when the time interval between the current time point and the historical time point is equal to a preset display period, all credit data of all mechanisms to be evaluated are obtained again, and all service data and all credit data corresponding to all mechanisms to be evaluated are sent to a display terminal for displaying according to the sequence of all credit data.

According to a second aspect of the present application, there is provided a credit data generation apparatus, the apparatus including:

the system comprises an acquisition module, a classification module and a classification module, wherein the acquisition module is used for acquiring data to be classified of a mechanism to be classified based on the current classification requirement, and inquiring an appointed classification rule corresponding to the data to be classified in the classification rule according to a preset regular expression;

the computing module is used for determining a specified index value and a specified index attribute corresponding to the specified scoring rule in a preset database, and computing the credit score of the mechanism to be ranked according to the specified index value and the specified index attribute;

the determining module is used for inquiring a plurality of preset score intervals in the current rating requirement, determining a target preset score interval in which the credit score hits in the preset score intervals, and taking the credit level corresponding to the target preset score interval as the credit data of the mechanism to be rated;

and the display module is used for sending the credit data to the terminal corresponding to the mechanism to be evaluated for display.

Optionally, the obtaining module is configured to obtain basic information uploaded by the to-be-rated mechanism based on the current rating requirement, and compare the basic information with the current rating requirement to obtain a first comparison result; when the first comparison result indicates that the basic information does not meet the current rating requirement, generating an audit failure prompt and sending the audit failure prompt to the to-be-rated mechanism for displaying, wherein the audit failure prompt is used for indicating the to-be-rated mechanism to upload the basic information again; and when the first comparison result indicates that the basic information meets the rating requirement, calling an external system connection interface, acquiring abnormal information of the mechanism to be rated, and extracting the rating content indicated by the current rating requirement from the basic data and the abnormal information to serve as the data to be rated.

Optionally, the calculation module is configured to query name tags of all index values and all index attributes in the preset database, and extract the index values and the index attributes of which the name tags are the same as the specified scoring rules as the specified index values and the specified index attributes; comparing the data to be graded with the specified grading rule to obtain a second comparison result, inquiring a specified index number value hit by the second comparison result, and taking the specified index number value as the initial grading; and extracting a score proportion from the specified index attribute corresponding to the specified index value, calculating the product of the score proportion and the initial score, and taking the product as the credit score of the mechanism to be rated.

Optionally, the apparatus further comprises:

the comparison module is used for comparing the credit data with a first preset grade threshold value to generate a third comparison result, and adding a display label to the mechanism to be evaluated corresponding to the credit data based on the third comparison result;

the extraction module is used for identifying the display label of the mechanism to be identified, extracting the mechanism to be identified with the display label content as excitation to form a credit red list, and extracting the mechanism to be identified with the display label content as correction to form a credit black list;

and the sending module is used for sending the credit red list and the credit blacklist to a display terminal database so that the display terminal calls the display list in the display terminal database for display.

Optionally, the comparison module is configured to add a display tag with content as an incentive to the mechanism to be rated corresponding to the credit data if the third comparison result indicates that the credit data is greater than or equal to the first preset level threshold; and if the third comparison result indicates that the credit data is smaller than the first preset level threshold, comparing the credit data with a second preset level threshold to obtain a fourth comparison result, and adding a display label with the corrected content to the mechanism to be evaluated corresponding to the credit data when the fourth comparison result indicates that the credit data is smaller than the second preset level threshold.

Optionally, the apparatus further comprises:

the data auditing module is used for responding to the credit complaint request triggered by the to-be-graded mechanism, acquiring to-be-graded data uploaded by the to-be-graded mechanism and auditing the credit to obtain an auditing result;

and the data deleting module is used for calling a display database of the display terminal when the auditing result indicates that the to-be-audited data meet the auditing specification, deleting the organization name of the to-be-rated organization in the display database, and finishing the display of the to-be-rated organization in the credit blacklist.

Optionally, the apparatus further comprises:

the system comprises a sequencing module, a display terminal and a rating evaluation module, wherein the sequencing module is used for acquiring credit data of all mechanisms to be rated, acquiring a plurality of credit data, sequencing the credit data from high to low according to numerical values, and sending service data and the credit data corresponding to all the mechanisms to be rated after sequencing to the display terminal for display, wherein the service data are all operation data corresponding to the mechanisms to be rated;

the statistical module is used for counting the current time point and determining the historical time point for displaying the service data and the credit data corresponding to the mechanism to be evaluated at the last time;

and the sequencing module is further used for re-acquiring all credit data of all mechanisms to be evaluated when the time interval between the current time point and the historical time point is equal to a preset display period, and sending all service data and all credit data corresponding to all mechanisms to be evaluated to a display terminal for displaying according to the sequencing of all credit data.

According to a third aspect of the present application, there is provided a computer device comprising a storage device, a processor and a computer program stored on the storage device and executable on the processor, the processor implementing the steps of the method according to any one of the first aspect when the program is executed.

According to a fourth aspect of the present application, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of any of the first aspects described above.

According to the technical scheme, the credit data generation method and the device provided by the application are characterized in that the data to be rated of the mechanism to be rated is obtained based on the current rating requirement, and the specified rating rule corresponding to the data to be rated is inquired in the rating rule according to the preset regular expression. And then, determining an appointed index value and an appointed index attribute corresponding to the appointed grading rule in a preset database, and calculating the credit score of the mechanism to be graded according to the appointed index value and the appointed index attribute. And then, inquiring a plurality of preset score intervals in the current rating requirement, determining a target preset score interval with the credit score hitting in the preset score intervals, and taking the credit level corresponding to the target preset score interval as the credit data of the mechanism to be rated. And finally, sending the credit data to a terminal corresponding to the mechanism to be evaluated for display. Based on basic information uploaded by the mechanism to be rated and abnormal information read from other systems, the credit score of the mechanism to be rated is automatically calculated, the credit grade hit by the credit score is used as credit data with the rating mechanism, automatic generation of the credit data is achieved, the transmission accuracy of the data to be rated is improved, and then the generation efficiency of the credit data is improved.

The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

fig. 1 is a schematic flowchart illustrating a credit data generation method according to an embodiment of the present application;

FIG. 2 is a flow chart of a credit data generation method according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram illustrating a credit data generation apparatus according to an embodiment of the present application;

fig. 4 shows a schematic device structure diagram of a computer apparatus according to an embodiment of the present application.

Detailed Description

Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

An embodiment of the present application provides a credit data generation method, as shown in fig. 1, the method includes:

101. and acquiring the data to be rated of the mechanism to be rated based on the current rating requirement, and inquiring an appointed rating rule corresponding to the data to be rated in the rating rule according to a preset regular expression.

102. And determining an appointed index value and an appointed index attribute corresponding to the appointed grading rule in a preset database, and calculating the credit score of the mechanism to be graded according to the appointed index value and the appointed index attribute.

103. Inquiring a plurality of preset score intervals in the current rating requirement, determining a target preset score interval with the credit score hitting in the preset score intervals, and taking the credit level corresponding to the target preset score interval as the credit data of the mechanism to be rated.

104. And sending the credit data to a terminal corresponding to the mechanism to be evaluated for display.

According to the method provided by the embodiment of the application, the data to be rated of the mechanism to be rated is acquired based on the current rating requirement, and the specified rating rule corresponding to the data to be rated is inquired in the rating rule according to the preset regular expression. And then, determining an appointed index value and an appointed index attribute corresponding to the appointed grading rule in a preset database, and calculating the credit score of the mechanism to be graded according to the appointed index value and the appointed index attribute. Then, a plurality of preset score intervals are inquired in the current rating requirement, a target preset score interval with the credit score hitting in the preset score intervals is determined, and the credit level corresponding to the target preset score interval is used as credit data of the mechanism to be rated. And finally, sending the credit data to a terminal corresponding to the mechanism to be evaluated for display. Based on basic information uploaded by the mechanism to be rated and abnormal information read from other systems, the credit score of the mechanism to be rated is automatically calculated, the credit grade hit by the credit score is used as credit data with the rating mechanism, automatic generation of the credit data is achieved, the transmission accuracy of the data to be rated is improved, and then the generation efficiency of the credit data is improved.

An embodiment of the present application provides a credit data generation method, as shown in fig. 2, the method includes:

201. and acquiring the data to be rated of the mechanism to be rated based on the current rating requirement, and inquiring an appointed rating rule corresponding to the data to be rated in the rating rule according to a preset regular expression.

With the continuous development of internet technology and the gradual progress of medical level, a third party payment mechanism is introduced in medical insurance management and operation, so that the impulse of inducing excessive supply or excessive consumption of medical insurance participants of fixed-point medical institutions or fixed-point retail drug stores is increased on the basis of effectively guaranteeing the medical insurance rights and interests of the participants, and even the risk of cheating the medical insurance fund by using various cheating means is increased. Therefore, at present, many platforms can build an integrity system for medical institutions, generate credit management operation procedures, generate credit data of the medical institutions, perform credit management on the medical institutions, and reduce the risk of cheating on medical insurance funds. At present, related staff participating in credit evaluation in a platform need to perform activities such as offline inquiry, research, inspection and the like, and finally data collection and sorting are performed on offline inquired data, and the offline inquired data are summarized into an integrity system to be scored, so that credit data of a medical institution are generated. However, the applicant recognizes that the platform dispatches a large amount of manpower to collect relevant data offline, and the manual offline data collection causes data loss, recording errors and the like, so that the data used for scoring is deviated from the actual situation of the medical institution, and the generation efficiency and accuracy of the credit data are low.

Therefore, according to the credit data generation method and device provided by the application, the data to be rated of the mechanism to be rated is obtained based on the current rating requirement, and the specified rating rule corresponding to the data to be rated is inquired in the rating rule according to the preset regular expression. And then, determining an appointed index value and an appointed index attribute corresponding to the appointed grading rule in a preset database, and calculating the credit score of the mechanism to be graded according to the appointed index value and the appointed index attribute. Then, a plurality of preset score intervals are inquired in the current rating requirement, a target preset score interval with the credit score hitting in the preset score intervals is determined, and the credit level corresponding to the target preset score interval is used as credit data of the mechanism to be rated. And finally, sending the credit data to a terminal corresponding to the mechanism to be evaluated for display. Based on basic information uploaded by the mechanism to be rated and abnormal information read from other systems, the credit score of the mechanism to be rated is automatically calculated, the credit grade hit by the credit score is used as credit data with the rating mechanism, automatic generation of the credit data is achieved, the transmission accuracy of the data to be rated is improved, and then the generation efficiency of the credit data is improved.

The system is suitable for a medical auditing platform, so that when relevant auditing workers audit medical credit of an organization to be rated, the credit rating of the organization to be rated can be completed by automatically detecting data to be rated of the organization to be rated and further generating credit data.

In the embodiment of the application, the data to be rated comprises the basic information and the abnormal information of the mechanism to be rated, so that the system firstly receives the basic information uploaded by the mechanism to be rated and compares the basic information with the rating requirement. That is, the system needs to determine whether the basic information uploaded by the organization to be rated is sufficient by using the rating requirement. Based on the comparison result, acquiring abnormal information of the mechanism to be rated, extracting content indicated by the rating requirement from the abnormal information and the basic information as data to be rated, and acquiring the data to be rated as follows:

firstly, acquiring basic information uploaded by an organization to be rated based on the current rating requirement, wherein the basic information comprises organization information, credit commitment information and good operation information of the organization to be rated. In fact, the system may call an information filling template corresponding to the current rating requirement based on the current rating requirement, and send the information filling template to the terminal of the to-be-rated organization, so that the to-be-rated organization uploads the basic information according to the information filling model. Such as corporate or non-corporate organization names, unified social credit codes, types, dates of establishment, addresses, business territories and legal representatives, principal names, job title and identity document types and contact details, and the like. In the practical application process, the organization to be evaluated needs to report good operation information and credit commitment information on an information filling interface. In addition, the system can set a submission entrance on the information filling interface, when the system detects that the submission key is triggered, the system receives the basic information, generates a submission success prompt after successfully receiving the basic information and sends the submission success prompt to the mechanism to be evaluated, and the method and the system for acquiring the basic information do not specifically limit the acquisition mode and the acquisition content of the basic information.

And then, comparing the basic information with the rating requirement, specifically, verifying the basic information by the system by using a rating index item stored in the rating requirement, and judging whether the content filled in the basic information meets the information category required to be filled in the rating index item, namely, if the profit value represented in the rating requirement needs to be uploaded by using digital information but the basic information is filled in by using text information, the verification result indicates that the current rating requirement is not met. And when the basic information does not meet the current rating requirement, generating an audit failure prompt and sending the audit failure prompt to an organization to be rated for displaying. It should be noted that the audit failure prompt is used to instruct the to-be-rated organization to upload the basic information again, that is, when the to-be-rated organization receives the audit failure prompt, the basic information needs to be refilled and uploaded. When the audit result indicates that the basic information meets the rating requirement, the system calls an external system connection interface to be connected with an external system, such as a business system, an intelligent supervision system, an audit system, an administrative penalty management system and the like. Further, in a database corresponding to the external system, the name of the organization to be rated or the unified social credit code is used for inquiring to obtain the abnormal information of the organization to be rated.

And finally, inquiring the specified item identification needing to be audited in the rating requirement, and extracting the rating content corresponding to the specified item identification from the basic data and the abnormal information, namely, the rating content indicated by the current rating requirement is taken as the data to be rated. And inquiring a specified grading rule corresponding to the data to be graded in the grading rule based on a preset regular expression. For example, the current rating requirement indicates that credit evaluation is performed on the drug supply and sale conditions of the fixed-point medical institution a, the drug unit price, the drug source and the drug sale quantity of the fixed-point medical institution a need to be checked, and the system can extract relevant contents of the drug unit price, the drug source and the drug sale quantity from the basic information and the abnormal information as data to be rated.

Through the steps, the basic information uploaded by the mechanism to be evaluated can be ensured to conform to the specified format, so that the auditing efficiency can be accelerated, the mechanism to be evaluated is connected with an external system after the preliminary auditing is passed, data interconnection is realized, the abnormal information corresponding to the mechanism to be evaluated is automatically acquired, errors caused by manual input of a large amount of information are avoided, and the accuracy of generating credit data for the mechanism to be evaluated is improved.

202. And determining an appointed index value and an appointed index attribute corresponding to the appointed grading rule in a preset database, and calculating the credit score of the mechanism to be graded according to the appointed index value and the appointed index attribute.

In the embodiment of the application, the preset database stores preset scoring rules, it should be noted that different rating requirements correspond to different scoring rules, actually, the scoring rules may use default scoring rules of the system, or may be set by related staff according to specific working scenes, and the setting mode and the setting content of the scoring rules are not specifically limited. For example, the rating rules of the hospitalization class do not require strict auditing of the numerical value of the drug sales, whereas the rating rules of the drug supply class require strict auditing of the numerical value of the drug sales. It should be noted that the scoring rule stores index values and index data, sources of the index values and the index data include, but are not limited to, offline access manual entry, data background import, automatic docking of other business systems, and the like. And calculating the credit score of the mechanism to be graded according to the designated index value and the designated index attribute.

Specifically, name tags of all index values and all index attributes are inquired in a preset database, and the index values and the index attributes of which the name tags are the same as the designated scoring rules are extracted to serve as the designated index values and the designated index attributes. And comparing the data to be graded with the specified grading rule to generate a second comparison result. In the practical application process, different information items in the data to be rated correspond to different specified rating rules, so that each information item corresponds to one comparison result, all the comparison results in the data to be rated are aggregated to obtain a final second comparison result, then specified index values hit by the second comparison result are inquired, and the specified index values are used as initial ratings. And finally, extracting the score ratio from the designated index attribute corresponding to the designated index value, calculating the product of the score ratio and the initial score, and taking the product as the credit score of the mechanism to be graded.

The method comprises the steps of obtaining scoring rules corresponding to different grading requirements, comparing data to be graded with the corresponding scoring rules to obtain initial scores of mechanisms to be graded, and carrying out scoring correction on the initial scores of the mechanisms to be graded according to different scoring ratios corresponding to different index values to obtain credit scores of the mechanisms to be graded, so that the accuracy of generating the credit data can be greatly improved.

203. Inquiring a plurality of preset score intervals in the current rating requirement, determining a target preset score interval with the credit score hitting in the plurality of preset score intervals, and taking the credit grade corresponding to the target preset score interval as the credit data of the mechanism to be rated.

In the embodiment of the application, a plurality of preset score intervals are defined in the rating requirement to judge which credit level the credit score of the organization to be rated is in, so that the system can identify the current rating requirement after obtaining the credit score, read the plurality of preset score intervals in the current rating requirement, determine a target preset score interval in which the credit score hits, and use the credit level corresponding to the target interval as the credit data of the organization to be rated. Further, the credit data is compared with a first preset level threshold and a second preset level threshold, and a display list where the current credit data is located is judged.

Specifically, the credit data is compared with a first preset grade threshold value to generate a third comparison result, and a display label is added to the mechanism to be rated corresponding to the credit data based on the third comparison result. In the practical application process, if the third comparison result indicates that the credit data is greater than or equal to the first preset level threshold, adding a display label with content as incentive to the mechanism to be rated corresponding to the credit data. And if the third comparison result indicates that the credit data is smaller than the first preset level threshold, comparing the credit data with the second preset level threshold to obtain a fourth comparison result, and adding a display label with the corrected content to the mechanism to be rated corresponding to the credit data when the fourth comparison result indicates that the credit data is smaller than the second preset level threshold.

Identifying the display label of the mechanism to be identified, extracting the mechanism to be identified with the display label content as the incentive to form a credit red list, and extracting the mechanism to be identified with the display label content as the correction to form a credit black list. And then, sending the credit red list and the credit blacklist to a display terminal database so that the display terminal calls the data in the display terminal database for display.

Through the steps, the credit data is compared with a first preset grade threshold value, whether the mechanism to be evaluated corresponding to the current credit data meets the condition of entering a red list or not is judged, if the mechanism to be evaluated corresponding to the current credit data does not meet the condition of entering the red list, the credit data is compared with a second preset grade threshold value, whether the mechanism to be evaluated corresponding to the current credit data meets the condition of entering a black list or not is judged, and the mechanisms to be evaluated in the red list and the black list are disclosed, so that the mechanisms to be evaluated in the black list are correspondingly rectified.

204. And sending the credit data to an organization to be rated for display.

In the embodiment of the application, the system sends the credit data and the red and black lists to the organization to be evaluated for display. In fact, for the organization to be evaluated which is already listed in the blacklist, when relevant organizations or personnel make an adjustment, the loss of credit behavior is corrected, and adverse effects are eliminated, a credit repair application can be provided, and if the audit is passed, the credit repair is carried out for the organization to be evaluated, and the blacklist disclosure time is ended.

Specifically, in response to a credit complaint request triggered by the mechanism to be evaluated, the to-be-evaluated data uploaded by the mechanism to be evaluated is acquired and subjected to credit evaluation, and an evaluation result is obtained. In a specific implementation scenario, a complaint entry may be set, for example, a "complaint" key is set, when the system detects that the "complaint" key is triggered, the system jumps to a complaint interface, and an organization to be rated may enter and submit relevant complaint information on the complaint interface. Further, the system sends the relevant complaint information to the auditing platform for displaying, and the auditing result uploaded by the auditing platform is obtained. Specifically, the auditing platform can establish an offline supervision team to perform offline auditing on the to-be-evaluated organization which proposes the complaint, and upload the auditing result. And then, when the audit result indicates that the data to be audited meet the audit specification, calling a display database of the display terminal, deleting the organization name of the organization to be rated in the display database, and finishing the display of the organization to be rated in the credit blacklist.

In another implementation scenario, the system acquires credit data of all mechanisms to be evaluated to obtain a plurality of credit data, sorts the credit data according to the sequence of numerical values from high to low, and respectively acquires service data of corresponding mechanisms to be evaluated according to the sorting to obtain all service data of all the mechanisms to be evaluated. In the practical application process, after the system obtains all the service data, a credit report can be generated based on all the service data and all the credit data, and then the credit report is sent to the medical auditing platform for displaying. Specifically, the credit report may include two topics of system operation and distrust analysis, for example, the operation condition of the credit evaluation system service is displayed, including the number of institutions to be evaluated accessed by the system, the number of supervising physicians/pharmacists, the annual credit evaluation completion condition, the integrity service acceptance certificate signing condition, and the development condition of the medical insurance loan service. And displaying violation behavior data of the organization to be evaluated, the medical insurance doctor and the medical insurance pharmacist, including the number of violation individuals and related violation amount, by the confidence losing analysis theme, and performing ranking display according to the violation severity. In fact, the content included in the credit report may be a theme default for the system, or may be a theme set by the relevant staff according to a specific implementation scenario, and the display content of the credit report is not specifically limited in the present application. Further, counting the current time point, and determining the historical time point for displaying the business data and the credit data corresponding to the mechanism to be graded last time. When the time interval between the current time point and the historical time point is equal to the preset display period, all credit data of all mechanisms to be evaluated are obtained again, all the mechanisms to be evaluated are sorted according to all the credit data, and all service data and all the credit data corresponding to all the mechanisms to be evaluated are sent to the display terminal for displaying according to the sorting.

Through the steps, the service data and the credit data of all the mechanisms to be evaluated are displayed on the terminal of the medical auditing platform, so that the medical auditing terminal can timely acquire the service data of the mechanisms to be evaluated, and the mechanism to be evaluated with low credit rating can be refined and improved.

Further, as a specific implementation of the method shown in fig. 1, an embodiment of the present application provides a credit data generation apparatus, and as shown in fig. 3, the apparatus includes: the system comprises an acquisition module 301, a calculation module 302, a determination module 303 and a presentation module 304.

The obtaining module 301 is configured to obtain data to be rated of a mechanism to be rated based on a current rating requirement, and query, in a rating rule, an assigned rating rule corresponding to the data to be rated according to a preset regular expression;

the calculating module 302 is configured to determine an assigned index value and an assigned index attribute corresponding to the assigned scoring rule in a preset database, and calculate a credit score of the to-be-rated organization according to the assigned index value and the assigned index attribute;

the determining module 303 is configured to query a plurality of preset score intervals in the current rating requirement, determine a target preset score interval in which the credit score hits in the plurality of preset score intervals, and use a credit level corresponding to the target preset score interval as credit data of the organization to be rated;

the display module 304 is configured to send the credit data to a terminal corresponding to the to-be-rated mechanism for display.

In a specific application scenario, the obtaining module 301 is configured to obtain basic information uploaded by the to-be-rated mechanism based on the current rating requirement, and compare the basic information with the current rating requirement to obtain a first comparison result; when the first comparison result indicates that the basic information does not meet the current rating requirement, generating an audit failure prompt and sending the audit failure prompt to the to-be-rated mechanism for displaying, wherein the audit failure prompt is used for indicating the to-be-rated mechanism to upload the basic information again; and when the first comparison result indicates that the basic information meets the rating requirement, calling an external system connection interface, acquiring abnormal information of the mechanism to be rated, and extracting the rating content indicated by the current rating requirement from the basic data and the abnormal information to serve as the data to be rated.

In a specific application scenario, the calculation module 302 is configured to query name tags of all index values and all index attributes in the preset database, and extract an index value and an index attribute, of which the name tags are the same as the specified scoring rule, as the specified index value and the specified index attribute; comparing the data to be graded with the specified grading rule to obtain a second comparison result, inquiring a specified index number value hit by the second comparison result, and taking the specified index number value as the initial grading; and extracting a score proportion from the specified index attribute corresponding to the specified index value, calculating the product of the score proportion and the initial score, and taking the product as the credit score of the mechanism to be rated.

In a specific application scenario, the apparatus further includes: a comparison module 305, an extraction module 306 and a sending module 307.

The comparison module 305 is configured to compare the credit data with a first preset level threshold, generate a third comparison result, and add a display tag to the mechanism to be rated corresponding to the credit data based on the third comparison result;

the extracting module 306 is configured to identify the display tag of the mechanism to be identified, extract the mechanism to be identified whose display tag content is excited to form a credit red list, extract the mechanism to be identified whose display tag content is modified to form a credit black list;

the sending module 307 is configured to send the credit red list and the credit blacklist to a display terminal database, so that the display terminal invokes the display list in the display terminal database to display.

In a specific application scenario, the comparing module 305 is configured to add a display tag with content as an incentive to the mechanism to be rated corresponding to the credit data if the third comparison result indicates that the credit data is greater than or equal to the first preset level threshold; and if the third comparison result indicates that the credit data is smaller than the first preset level threshold, comparing the credit data with a second preset level threshold to obtain a fourth comparison result, and adding a display label with the corrected content to the mechanism to be evaluated corresponding to the credit data when the fourth comparison result indicates that the credit data is smaller than the second preset level threshold.

In a specific application scenario, the apparatus further includes: a data auditing module 308 and a data deleting module 309.

The data auditing module 308 is configured to respond to the credit complaint request triggered by the to-be-rated organization, acquire to-be-audited data uploaded by the to-be-rated organization, and perform credit auditing to obtain an auditing result;

the data deleting module 309 is configured to, when the audit result indicates that the to-be-audited data meets the audit specification, call a display database of the display terminal, delete the organization name of the to-be-rated organization in the display database, and end the display of the to-be-rated organization on the credit blacklist.

In a specific application scenario, the apparatus further includes: a sorting module 310 and a statistics module 311.

The ranking module 310 is configured to obtain credit data of all organizations to be ranked, obtain a plurality of credit data, rank the credit data in a descending order of numerical values, and send service data and the credit data corresponding to all the ranked organizations to a display terminal for display, where the service data is all operation data corresponding to the organizations to be ranked;

the statistical module 311 is configured to count a current time point, and determine a historical time point at which service data and credit data corresponding to the to-be-rated organization are displayed last time;

the sorting module 310 is further configured to, when the time interval between the current time point and the historical time point is equal to a preset display period, re-acquire all credit data of all mechanisms to be evaluated, and send all service data and all credit data corresponding to all mechanisms to be evaluated to a display terminal for display according to the sorting of all credit data.

According to the device provided by the embodiment of the application, the data to be rated of the mechanism to be rated is acquired based on the current rating requirement, and the specified rating rule corresponding to the data to be rated is inquired in the rating rule according to the preset regular expression. And then, determining an appointed index value and an appointed index attribute corresponding to the appointed grading rule in a preset database, and calculating the credit score of the mechanism to be graded according to the appointed index value and the appointed index attribute. Then, a plurality of preset score intervals are inquired in the current rating requirement, a target preset score interval with the credit score hitting in the preset score intervals is determined, and the credit level corresponding to the target preset score interval is used as credit data of the mechanism to be rated. And finally, sending the credit data to a terminal corresponding to the mechanism to be evaluated for display. Based on basic information uploaded by the mechanism to be rated and abnormal information read from other systems, the credit score of the mechanism to be rated is automatically calculated, the credit grade hit by the credit score is used as credit data with the rating mechanism, automatic generation of the credit data is achieved, the transmission accuracy of the data to be rated is improved, and then the generation efficiency of the credit data is improved.

It should be noted that other corresponding descriptions of the functional units related to the credit data generation apparatus provided in the embodiment of the present application may refer to the corresponding descriptions in fig. 1 and fig. 2, and are not described again here.

In an exemplary embodiment, referring to fig. 4, there is further provided a device, which includes a bus, a processor, a memory, and a communication interface, and may further include an input/output interface and a display device, wherein the functional units may communicate with each other through the bus. The memory stores a computer program, and the processor executes the program stored in the memory to perform the credit data generation method in the above embodiment.

A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the credit data generation method.

Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by hardware, and also by software plus a necessary general hardware platform. Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, or the like), and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, or the like) to execute the method described in the implementation scenarios of the present application.

Those skilled in the art will appreciate that the figures are merely schematic representations of one preferred implementation scenario and that the blocks or flow diagrams in the figures are not necessarily required to practice the present application.

Those skilled in the art will appreciate that the modules in the devices in the implementation scenario may be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or may be located in one or more devices different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.

The above application serial number is merely for description and does not represent the superiority and inferiority of the implementation scenario.

The above disclosure is only a few specific implementation scenarios of the present application, but the present application is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present application.

Claims

1. A credit data generation method, comprising:

2. The method of claim 1, wherein the obtaining of the data to be rated of the organization to be rated based on the current rating requirement comprises:

3. The method according to claim 1, wherein the step of determining the designated index value and the designated index attribute corresponding to the designated scoring rule in a preset database, and calculating the credit score of the to-be-rated organization according to the designated index value and the designated index attribute comprises the following steps:

4. The method of claim 1, wherein after querying a plurality of preset score intervals in the current rating requirement, determining a target preset score interval in which the credit score hits in the plurality of preset score intervals, and using a credit level corresponding to the target preset score interval as credit data of the organization to be rated, the method further comprises:

and sending the credit red list and the credit blacklist to a display terminal database so that the display terminal calls the display list in the display terminal database for display.

5. The method according to claim 4, wherein the adding a display tag to the to-be-rated organization corresponding to the credit data based on the third comparison result comprises:

if the third comparison result indicates that the credit data is greater than or equal to the first preset grade threshold value, adding a display label with content as excitation to the mechanism to be rated corresponding to the credit data;

6. The method according to claim 1, wherein after the credit data is sent to a terminal corresponding to the organization to be rated for display, the method further comprises:

7. The method of claim 1, further comprising:

acquiring credit data of all organizations to be rated to obtain a plurality of credit data, sequencing the credit data according to the numerical value from high to low, and sending service data and the credit data corresponding to all the sequenced organizations to be rated to a display terminal for displaying, wherein the service data are all operation data corresponding to the organizations to be rated;

8. A credit data generation device, comprising:

the calculation module is used for determining the appointed index value and the appointed index attribute corresponding to the appointed grading rule in a preset database, and calculating the credit score of the mechanism to be graded according to the appointed index value and the appointed index attribute;

9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.